Awards

See Archive for past awards.

Each year the conference Program Committee presents the best paper awards and the best student paper awards. The Steering Committee presents two special awards - The Most Influential Paper award and the Most Distinguished Contribution award.

PAKDD 2011 Awards 25 May 2011

• Best Research Paper Zhongwu Zhai, Bing Liu, Hua Xu and Peifa Jia. Constrained LDA for Grouping Product Features in Opinion Mining


• Best Research Paper Runner Up Nenad Tomašev, Milos Radovanovic, Dunja Mladenic and Mirjana Ivanovic. The Role of Hubness in Clustering High-Dimensional Data


• Best Application Paper U Kang, Brendan Meeder and Christos Faloutsos. Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation

PAKDD Most Influential Paper Award 2011 (PAKDD 2001) 25 May 2011

The candidates for the Most Influential Paper Award are those papers published at this conference ten years ago. A review of citations is undertaken to identify a pool of candidates, followed by a challenger/champion approach used by the awards committee to identify the winning paper. The award began with the tenth anniversary of this conference series.

This year's candidates were drawn from the 5th PAKDD conference, held in Hong Kong, China, in 2001. The winner was:

Evaluation of Interestingness Measures for Ranking Discovered Knowledge by Robert J. Hilderman and Howard J. Hamilton. Lecture Notes In Computer Science, Vol 2035. Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2001. Pages 247 - 259. This paper introduced a new framework for considering how we measure the interestingness of discoveries, and has been adopted widely by other researchers.

PAKDD Distinguished Contribution Award 2010 25 May 2011

The Distinguished Contribution Award is awarded to a KDD researcher to recognise and honour an individual who has made significant and continued contributions in research and services to the advancement of the PAKDD conferences.

The 2011 award for Most Distinguished Contribution went to Professor Graham Williams, Director and Senior Data Miner of the Australian Taxation Office, and Adjunct Professor, Australian National University, University of Canberra, and Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. Graham is a key supporter of PAKDD and has made significant contribution to PAKDD since the inauguration of the conference. He has served in many roles in the PAKDD conference series. He has been the Steering Committee Co-Chair and Treasurer since 2001. He was the Organization Committee Chair of PAKDD 1998, Program Co-Chair of PAKDD 2001, Industrial Chair of PAKDD 2004 and the Tutorial Chair of PAKDD 2007. He is also the founder and Steering Committee Co-Chair of the Australasian Data Mining Conference series. Graham has made significant technical contributions with considerable success in the application of data mining technology to real world problems. His pivotal role in deploying data mining in industry was recognised by the Australian Taxation Office with an Innovation Award in 2006 and an Australia Day award in 2007. Graham has published extensively in data mining in many important conferences and journals. He is the author of the immensely popular open source Rattle data mining software and a keen advocate of freely sharing research software. His Internet book Data Mining Desktop Survival Guide is a highly popular tool book for data mining practitioners and this will be published shortly under the title Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discover, by Springer.

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Last Modified 2011-06-03 09:45:24 Graham Williams
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